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Add ExecuTorch WebGPU program for modnet
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---
license: apache-2.0
library_name: executorch
pipeline_tag: image-segmentation
tags:
- executorch
- webgpu
- on-device
- browser
---
# MODNet portrait matting for ExecuTorch WebGPU
This repository contains an [ExecuTorch](https://github.com/pytorch/executorch) conversion of
https://github.com/ZHKKKe/MODNet for the ExecuTorch **WebGPU** backend, so the model runs entirely in a web browser on
the visitor's GPU. It powers the corresponding demo in the
ExecuTorch WebGPU Playground (launching soon on [executorch.ai](https://executorch.ai)).
- **Base model:** https://github.com/ZHKKKe/MODNet
- **Format:** ExecuTorch `.pte` programs delegated to the WebGPU backend
- **Quantization:** fp32 (as exported)
- **Total size:** 24.9 MB
## Files
| File | Size | SHA-256 |
|---|---|---|
| `modnet_webgpu.pte` | 24.9 MB | `0c2ff92e26087e98…` |
Full checksums are in `manifest.json`. The playground verifies them after download.
## Running it
These programs need the ExecuTorch WebGPU runtime compiled to WebAssembly
([backends/webgpu](https://github.com/pytorch/executorch/tree/main/backends/webgpu)). The easiest way to
try the model is the ExecuTorch WebGPU Playground (launching soon on [executorch.ai](https://executorch.ai)),
which downloads these files once, caches them in the browser, and runs everything locally.
## Provenance
- **Weights:** `boopathiraj/MODNet` @ `a967175f8fd63de67a1c161d8daac966d2b57e3a`, file `modnet/pretrained/modnet_photographic_portrait_matting.ckpt`, sha256 `7c22235f0925deba15d4d63e53afcb654c47055bbcd98f56e393ab2584007ed8` (from a community mirror of the official release)
- **Exported with:** executorch 1.5.1+cpu, torch 2.14.1+cpu, torchao 0.18.0+cpu, transformers 5.19.0 (executorch git `3b6068392324`)
- **Reproduce:** `python recipes/modnet.py --out out/modnet` (recipe in `export/`)
- Re-running the recipe produces byte-identical files.
## License
This is a derivative of the upstream model and is distributed under the same terms
(`apache-2.0`); see `LICENSE`.
Modifications (conversion to the ExecuTorch format and quantization) by Meta Platforms, Inc.